Automated tongue segmentation is a critical component of tongue diagnosis, especially in Traditional Chinese Medicine (TCM), where it has been practiced for thousands of years and is generally considered pain-free and non-invasive. Therefore, a more precise, fast, and robust tongue segmentation system to automatically segment tongue images from its raw format is necessary. Previous algorithms segmented the tongue in different ways, where the results are either inaccurate or time-consuming. Furthermore, none of them developed a dedicated, automatic segmentation system. In this paper, we proposed TongueNet, which is a precise and fast automatic tongue segmentation system. U-net is utilized as the segmentation backbone applying a small-scale image dataset. Besides this, a morphological layer is proposed in the latter stages of the architecture. The proposed system when applied to a tongue image dataset with 1000 images, achieved the highest Pixel Accuracy of 98.45% and consumed 0.267 s per picture on average, which outperformed conventional state-of-the-art tongue segmentation methods in both accuracy and speed. Extensive qualitative and quantitative experiments showed the robustness of the proposed system concerning different positions, poses, and shapes. The results indicate a promising step in achieving a fully automated tongue diagnosis system.

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The uncertainty of wind resources is one of the main reasons for wind abandonment. Considering the uncertainty of wind power prediction, a robust optimal dispatching model is proposed for the wind fire energy storage system with advanced adiabatic compressed air energy storage (AA-CAES) technology. Herein, the operation constraints of the power plant and constraints of the reserved capacity are defined according to the operation characteristics of AA-CAES. Based on the limited scenario method, a solution framework is proposed to achieve the optimal robustness and economical operation of the system, which provides a new way for the application of the intelligent algorithm in the robust optimal dispatching. Specifically, a novel equilibrium optimization algorithm is employed to solve the optimal dispatching problem, which has good global search performance. The proposed solution is validated through simulations based on the IEEE-39 node system. The simulation results verify the effectiveness of the proposed dispatching model and the intelligent solver.

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